Datafront Skill Surge: Unlocking policy insights through data integration

Course description

What do we mean when we talk about administrative data? Why is administrative data considered such a powerful tool?

Routinely collected administrative data captures interactions across the entire population, offering an unparalleled breadth and depth of information.

This on-demand series aims to equip researchers with the knowledge and skills to harness data for societal and sustainable change. This series covers important topics such as the use of administrative data in policymaking, circular economy models, climate resilience, and the impact of digital media on behaviour, with emphasis on the importance of interdisciplinary collaboration and innovative strategies to address global challenges.

Participants will gain insights from experts, study case studies, and explore practical examples that illustrate how data-driven approaches and emerging technologies are transforming urban planning, agriculture, and health – that will empower researchers to shape the future of the data landscape!

• Session 3 will explore how integrating datasets across various sectors enables governments to gain comprehensive insights into societal issues. We’ll discuss techniques for data integration, best practices, challenges, and how this can drive proactive and evidence-based policy interventions.

 

Learning mode

On-demand, self-paced 

 

Who should attend

This course is intended for:

• Data Analysts and Researchers: Those working with administrative or big data who want to deepen their understanding of its characteristics and uses.
• Policymakers and Government Officials: Decision-makers who rely on data to shape public policies.
• Public Sector Managers: Managers in government institutions seeking to optimise data usage for service improvements.
• Health and Social Care Professionals: Individuals looking to use data for improving service delivery and outcomes.
• Urban Planners and Public Health Professionals: Individuals interested in using administrative data to inform planning and health policies.

 

Aims and objectives

• Introduce the concept of data integration and its importance in creating comprehensive datasets.
• Demonstrate methods for linking data across various sources, such as health, education, and social care.
• Highlight the challenges and ethical considerations in data integration.
• Show how integrated data enhances decision-making by providing a fuller picture of the population or issue under study.

 

Skills area and competencies

Based on the Datacise Open Learning framework, the relevant skills and competencies for this video include:

Skills Areas:

• Data Integration Techniques: Mastering the skills needed to combine datasets from various sources.
• Cross-Sector Data Linkage: Understanding how to link data from multiple domains (e.g., health, social care) while preserving privacy and integrity.
• Handling Big Data: Skills for managing and organising large, complex datasets effectively.

 

Competencies:

• Data Fusion: Competency in fusing different types of data (quantitative, qualitative, geographic) to create richer datasets.
• Data Validation and Quality Control: Skills in ensuring data accuracy and consistency during integration.
• Privacy and Ethics in Data Linkage: Understanding the privacy concerns and ethical considerations when combining sensitive data.

 

Pre-requisite

• Basic knowledge of data analysis and data management practices.
• Familiarity with administrative data or large datasets is recommended.
• An understanding of privacy and ethical issues related to data handling is beneficial.

 

Learning outcomes

• Understand the process of integrating data from multiple sources and the benefits it provides in research and decision-making.
• Identify the tools and techniques used for effective data integration.
• Recognise the ethical challenges involved in linking datasets, particularly concerning privacy and data protection.
• Appreciate the role of data integration in enhancing insights from administrative and research data.

 

Transferable skills

• Data Integration: Ability to combine data from various sources to create comprehensive, linked datasets.
• Data Quality Management: Skills in ensuring data accuracy and integrity during the integration process.
• Problem-Solving: Enhanced problem-solving skills when dealing with data discrepancies or integration challenges.
• Collaboration Skills: Ability to work across sectors (e.g., health, social care) to bring together disparate datasets.

 

Assessment

Multiple choice quiz to self-check understanding. 

 

This training content was originally developed and produced by Professor Adam Chee, Datacise Education Lead at Swansea University, with narration enhanced by advanced text-to-speech technology.